The molecular mechanisms of osteoarthritis, the most common chronic disease, remain unexplained. This study aimed to use bioinformatic methods to identify the key biomarkers and immune infiltration ...in osteoarthritis. Gene expression profiles (GSE55235, GSE55457, GSE77298, and GSE82107) were selected from the Gene Expression Omnibus database. A protein-protein interaction network was created, and functional enrichment analysis and genomic enrichment analysis were performed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) databases. Immune cell infiltration between osteoarthritic tissues and control tissues was analyzed using the CIBERSORT method. Identify immune patterns using the ConsensusClusterPlus package in R software using a consistent clustering approach. Molecular biological investigations were performed to discover the important genes in cartilage cells. A total of 105 differentially expressed genes were identified. Differentially expressed genes were enriched in immunological response, chemokine-mediated signaling pathway, and inflammatory response revealed by the analysis of GO and KEGG databases. Two distinct immune patterns (ClusterA and ClusterB) were identified using the ConsensusClusterPlus. Cluster A patients had significantly lower resting dendritic cells, M2 macrophages, resting mast cells, activated natural killer cells and regulatory T cells than Cluster B patients. The expression levels of TCA1, TLR7, MMP9, CXCL10, CXCL13, HLA-DRA, and ADIPOQSPP1 were significantly higher in the IL-1β-induced group than in the osteoarthritis group in an
in vitro
qPCR experiment. Explaining the differences in immune infiltration between osteoarthritic tissues and normal tissues will contribute to the understanding of the development of osteoarthritis.
Small and medium-sized businesses as well as individuals are increasingly using online crowdfunding platforms to raise funds in the fintech world. Creators of crowdfunding projects depend heavily on ...social networks like Facebook to publicize their projects. Social media activities such as “liking” on Facebook bring massive traffic to crowdfunding projects and attract contributions. Using data collected from Facebook and Kickstarter, our empirical tests demonstrate that social media activities significantly and positively impact the likely success of crowdfunding. Our duration model analysis reveals that the impact of social media activities on crowdfunding outcomes follows a J-curve in the temporal space. We explain the J-curve by identifying two important effects of social media activities throughout the crowdfunding process: a quality-signaling effect in the opening period and a herding effect in the closing period. Especially in the “last mile,” there is a strong herding effect that helps crowdfunding projects reach their respective fundraising goals. Our results offer useful contributions to the literature and suggestions for practitioners.
The aim of this study is to develop a nomogram model for predicting the occurrence of intramyocardial hemorrhage (IMH) in patients with Acute Myocardial Infarction (AMI) following Percutaneous ...Coronary Intervention (PCI). The model is constructed utilizing clinical data and the SYNTAX Score (SS), and its predictive value is thoroughly evaluated.
A retrospective study was conducted, including 216 patients with AMI who underwent Cardiac Magnetic Resonance (CMR) within a week post-PCI. Clinical data were collected for all patients, and their SS were calculated based on coronary angiography results. Based on the presence or absence of IMH as indicated by CMR, patients were categorized into two groups: the IMH group (109 patients) and the non-IMH group (107 patients). The patients were randomly divided in a 7:3 ratio into a training set (151 patients) and a validation set (65 patients). A nomogram model was constructed using univariate and multivariate logistic regression analyses. The predictive capability of the model was assessed using Receiver Operating Characteristic (ROC) curve analysis, comparing the predictive value based on the area under the ROC curve (AUC).
In the training set, IMH post-PCI was observed in 78 AMI patients on CMR, while 73 did not show IMH. Variables with a significance level of P < 0.05 were screened using univariate logistic regression analysis. Twelve indicators were selected for multivariate logistic regression analysis: heart rate, diastolic blood pressure, ST segment elevation on electrocardiogram, culprit vessel, symptom onset to reperfusion time, C-reactive protein, aspartate aminotransferase, lactate dehydrogenase, creatine kinase, creatine kinase-MB, high-sensitivity troponin T (HS-TnT), and SYNTAX Score. Based on multivariate logistic regression results, two independent predictive factors were identified: HS-TnT (Odds Ratio OR = 1.61, 95% Confidence Interval CI: 1.21-2.25, P = 0.003) and SS (OR = 2.54, 95% CI: 1.42-4.90, P = 0.003). Consequently, a nomogram model was constructed based on these findings. The AUC of the nomogram model in the training set was 0.893 (95% CI: 0.840-0.946), and in the validation set, it was 0.910 (95% CI: 0.823-0.970). Good consistency and accuracy of the model were demonstrated by calibration and decision curve analysis.
The nomogram model, constructed utilizing HS-TnT and SS, demonstrates accurate predictive capability for the risk of IMH post-PCI in patients with AMI. This model offers significant guidance and theoretical support for the clinical diagnosis and treatment of these patients.
Background
Left atrial (LA) strain is associated with structural remodeling of the LA. Whether there is an association between LA strain obtained by cardiac magnetic resonance imaging (MRI) and ...new‐onset atrial fibrillation (AF) after ST‐segment elevation myocardial infarction (STEMI) is unclear.
Purpose
To investigate the relationship between LA strain and new‐onset AF after STEMI.
Study Type
Retrospective.
Population
Three hundred and seventy‐nine STEMI patients were enrolled, of which 26 had new‐onset AF.
Field Strength/Sequence
3.0 T, balanced turbo field echo sequence.
Assessment
Patients were divided into w/o AF group and new‐onset AF group. Cardiac MRI images were analyzed using cardiovascular imaging software CVI 42 (Circle Cardiovascular Imaging, Canada). An automatic tracing algorithm was applied to obtain strain values. The reservoir strain, conduit strain, and booster strain were included in model 1, model 2, and model 3, respectively.
Statistical Tests
Student's t‐test, Mann–Whiney U test, and chi‐square test were performed. Variables with a P ≤ 0.05 were incorporated into the logistic regression analysis. Area under curve of receiver operating characteristic was used to assess the ability of LA strain to identify new‐onset AF. Bayesian information criterion, Akaike information criterion, and C‐index were used to make comparisons between three models. P < 0.05 was considered statistically significant.
Results
Three models were used to assess LA strain identification ability for new‐onset AF. After including multiple factors, right coronary artery (RCA), LVEF, and reservoir strain were still risk factors for new‐onset AF in model 1. In model 2, age, RCA, LVEF, and conduit strain were still risk factors for new‐onset AF. In model 3, RCA, LVEF, LVEDVi, and booster strain were still risk factors for new‐onset AF. Model 2 has a stronger identification ability than others.
Data Conclusion
LA strain associated with new‐onset AF after STEMI. The model including conduit strain was the best‐fit one.
Level of Evidence
4
Technical Efficacy
Stage 3
The interaction between microplastics (MPs) and cadmium (Cd) poses a threat to agricultural soil environments, and their effects on plant growth and rhizosphere microbial community functions are not ...yet clear. In this study, energy sorghum was used as a test plant to investigate the effects of two types of MPs, polystyrene (PS) and polyethylene (PE), at different particle sizes (13 μm, 550 μm) and concentrations (0.1%, 1% w/w), and Cd, as well as their interactions, on the growth of sorghum in a soil-cultivation pot experiment. The results showed that the combined effects of MP and Cd pollution on the dry weight and Cd accumulation rate in sorghum varied depending on the type, concentration, and particle size of the MPs, with an overall trend of increasing stress from combined pollution with increasing Cd content and accumulation. High-throughput sequencing analysis revealed that combined MP and Cd pollution increased bacterial diversity, and the most significant increase was observed in the abundance-based coverage estimator (ACE), Shannon, and Sobs indices in the 13 μm 1% PS+Cd treatment group. Metagenomic analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways revealed that 19 groups of metabolic pathways, including microbial metabolism and methane metabolism, differed significantly under combined MP and Cd pollution. Hierarchical clustering results indicated that Cd treatment and combined MP and Cd treatment affected the abundances of sorghum rhizosphere soil nitrogen (N) and phosphorus (P) cycling genes and that the type of MP present was an important factor affecting N and P cycling genes. The results of this study provide a basis for exploring the toxic effects of combined MP and Cd pollution and for conducting soil environmental risk assessments.
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•Combined MP and Cd treatment tended to increase stress in sorghum plants.•Combined MP and Cd treatment increased Cd content and accumulation in sorghum.•Metagenomic analysis was used to determine the effects of combined MP and Cd treatment on rhizosphere microbial functions.•Combined MP and Cd treatment changed rhizosphere bacterial diversity and community composition.•Combined MP and Cd treatment altered microbial functions.
Chronic compressive spinal cord injury in compressive cervical myelopathy conditions can lead to rapid neurological deterioration in the early phase, followed by partial self-recovery, and ultimately ...an equilibrium state of neurological dysfunction. Ferroptosis is a crucial pathological process in many neurodegenerative diseases; however, its role in chronic compressive spinal cord injury remains unclear. In this study, we established a chronic compressive spinal cord injury rat model, which displayed its most severe behavioral and electrophysiological dysfunction at 4 weeks and partial recovery at 8 weeks after compression. Bulk RNA sequencing data identified enriched functional pathways, including ferroptosis, presynapse, and postsynaptic membrane activity at both 4 and 8 weeks following chronic compressive spinal cord injury. Transmission electron microscopy and malondialdehyde quantification assay confirmed that ferroptosis activity peaked at 4 weeks and was attenuated at 8 weeks after chronic compression. Ferroptosis activity was negatively correlated with behavioral score. Immunofluorescence, quantitative polymerase chain reaction, and western blotting showed that expression of the anti-ferroptosis molecules, glutathione peroxidase 4 (GPX4) and MAF BZIP transcription factor G (MafG), in neurons was suppressed at 4 weeks and upregulated at 8 weeks following spinal cord compression. There was a positive correlation between the expression of these two molecules, suggesting that they may work together to contribute to functional recovery following chronic compressive spinal cord injury. In conclusion, our study determined the genome-wide expression profile and ferroptosis activity of a consistently compressed spinal cord at different time points. The results showed that anti-ferroptosis genes, specifically GPX4 and MafG, may be involved in spontaneous neurological recovery at 8 weeks of chronic compressive spinal cord injury. These findings contribute to a better understanding of the mechanisms underlying chronic compressive spinal cord injury and may help identify new therapeutic targets for compressive cervical myelopathy.
Although clinically associated with severe developmental defects, the biological function of FOXK2 remains poorly explored. Here we report that FOXK2 interacts with transcription corepressor ...complexes NCoR/SMRT, SIN3A, NuRD, and REST/CoREST to repress a cohort of genes including HIF1β and EZH2 and to regulate several signaling pathways including the hypoxic response. We show that FOXK2 inhibits the proliferation and invasion of breast cancer cells and suppresses the growth and metastasis of breast cancer. Interestingly, FOXK2 is transactivated by ERα and transrepressed via reciprocal successive feedback by HIF1β/EZH2. Significantly, the expression of FOXK2 is progressively lost during breast cancer progression, and low FOXK2 expression is strongly correlated with higher histologic grades, positive lymph nodes, and ERα−/PR−/HER2- status, all indicators of poor prognosis.
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•FOXK2 is a transcription repressor•FOXK2 is physically associated with multiple corepressor complexes•FOXK2 and its associated corepressor complexes target the hypoxia pathway•FOXK2 suppresses the growth and metastasis of breast cancer
Shan et al. show that FOXK2 interacts with multiple corepressor complexes to repress the expression of a cohort of genes including HIF1β and EZH2. They show that an ERα-FOXK2-HIF1β/EZH2 axis is critically involved in breast cancer progression and that low FOXK2 expression correlates with poor prognosis.
Epigenetic regulation, particularly RNA n6 methyl adenosine (m6A) modification, plays an important role in the immune response. However, the regulatory role of m6A in the immune microenvironment in ...osteoarthritis (OA) remains unclear. Accordingly, we systematically studied RNA modification patterns mediated by 23 m6A regulators in 38 samples and discussed the characteristics of the immune microenvironment modified by m6A. Next, we constructed a novel OA m6A nomogram, an m6A-transcription factor-miRNA network, and a drug network. Healthy and OA samples showed distinct m6A regulatory factor expression patterns.
YTHDF3
expression was upregulated in OA samples and positively correlated with type II helper cells and
TGFb
family member receptors. Furthermore, three different RNA modification patterns were mediated by 23 m6A regulatory factors; in Mode 3, the expression levels of
YTHDF3
, type II T helper cells, and
TGFb
family member receptors were upregulated. Pathways related to endoplasmic reticulum oxidative stress and mitochondrial autophagy showed a strong correlation with the regulatory factors associated with Mode 3 and 23 m6A regulatory factors. Through RT-qPCR we validated that
SREBF2
and
EGR1
as transcription factors of
YTHDF3
and
IGF2BP3
are closely associated with the development of OA, hsa-miR-340 as a miRNA for
YTHDF3
and
IGF2BP3
was involved in the development of OA, we also detected the protein expression levels of
IGF2BP3
,
YTHDF3
,
EGR1
and
SREBF2
by western blotting, and the results were consistent with PCR. Overall, the constructed nomogram can facilitate the prediction of OA risk.
Acute ischemic stroke (AIS) is a common neurological disorder characterized by the sudden onset of cerebral ischemia, leading to functional impairments. Swift and precise detection of AIS lesions is ...crucial for stroke diagnosis and treatment but poses a significant challenge. This study aims to leverage multimodal fusion technology to combine complementary information from various modalities, thereby enhancing the detection performance of AIS target detection models.
In this retrospective study of AIS, we collected data from 316 AIS patients and created a multi-modality magnetic resonance imaging (MRI) dataset. We propose a Multi-Scale Attention-based YOLOv5 (MSA-YOLOv5), targeting challenges such as small lesion size and blurred borders at low resolutions. Specifically, we augment YOLOv5 with a prediction head to detect objects at various scales. Next, we replace the original prediction head with a Multi-Scale Swin Transformer Prediction Head (MS-STPH), which reduces computational complexity to linear levels and enhances the ability to detect small lesions. We incorporate a Second-Order channel attention (SOCA) module to adaptively rescale channel features by employing second-order feature statistics for more discriminative representations. Finally, we further validate the effectiveness of our method using the ISLES 2022 dataset.
On our in-house AIS dataset, MSA-YOLOv5 achieves a 79.0% mAP0.5, substantially surpassing other single-stage models. Compared to two-stage models, it maintains a comparable performance level while significantly reducing the number of parameters and resolution. On the ISLES 2022 dataset, MSA-YOLOv5 attains an 80.0% mAP0.5, outperforming other network models by a considerable margin. MS-STPH and SOCA modules can significantly increase mAP0.5 by 2.7% and 1.9%, respectively. Visualization interpretability results show that the proposed MSA-YOLOv5 restricts high attention in the small regions of AIS lesions.
The proposed MSA-YOLOv5 is capable of automatically and effectively detecting acute ischemic stroke lesions in multimodal images, particularly for small lesions and artifacts. Our enhanced model reduces the number of parameters while improving detection accuracy. This model can potentially assist radiologists in providing more accurate diagnosis, and enable clinicians to develop better treatment plans.
•A multi-scale attention-based YOLOv5 is proposed for detecting acute ischemic stroke.•Multi-modality images of DWI and ADC are integrated by a new data augmentation way.•A multi-scale Swin Transformer Prediction Head improves detections of small lesions.•A Second-Order attention module raises the ability of discriminative representation.•A mAP@0.5 of 79.0% and 80.0% is achieved in the in-house and ISLES 2022 datasets.
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